Triple

T7657809
Position Surface form Disambiguated ID Type / Status
Subject Helsingborg E173429 entity
Predicate hasSportsClub P346 FINISHED
Object Råå IF
Råå IF is a Swedish sports club based in the Helsingborg area, best known for its football team and long local tradition.
E679741 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Råå IF | Statement: [Helsingborg, hasSportsClub, Råå IF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Råå IF
Context triple: [Helsingborg, hasSportsClub, Råå IF]
  • A. Timrå IK
    Timrå IK is a professional ice hockey club from Timrå, Sweden, best known for competing in the country’s top leagues and developing numerous elite players.
  • B. Stattena IF
    Stattena IF is a Swedish football club known for its role in developing players such as renowned coach and former international striker Pia Sundhage.
  • C. Östers IF
    Östers IF is a Swedish football club based in Växjö, known for its history in the country’s top divisions and domestic successes.
  • D. Segeltorps IF
    Segeltorps IF is a Swedish multi-sport club best known for its ice hockey and football teams based in the Segeltorp area of Huddinge, near Stockholm.
  • E. Kjelsås IL
    Kjelsås IL is a Norwegian multi-sport club based in the Kjelsås neighborhood of Oslo, known for activities such as football, handball, and skiing.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Råå IF
Triple: [Helsingborg, hasSportsClub, Råå IF]
Generated description
Råå IF is a Swedish sports club based in the Helsingborg area, best known for its football team and long local tradition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Råå IF
Target entity description: Råå IF is a Swedish sports club based in the Helsingborg area, best known for its football team and long local tradition.
  • A. Timrå IK
    Timrå IK is a professional ice hockey club from Timrå, Sweden, best known for competing in the country’s top leagues and developing numerous elite players.
  • B. Stattena IF
    Stattena IF is a Swedish football club known for its role in developing players such as renowned coach and former international striker Pia Sundhage.
  • C. Östers IF
    Östers IF is a Swedish football club based in Växjö, known for its history in the country’s top divisions and domestic successes.
  • D. Segeltorps IF
    Segeltorps IF is a Swedish multi-sport club best known for its ice hockey and football teams based in the Segeltorp area of Huddinge, near Stockholm.
  • E. Kjelsås IL
    Kjelsås IL is a Norwegian multi-sport club based in the Kjelsås neighborhood of Oslo, known for activities such as football, handball, and skiing.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7019161548190855a5b1e9f5d7e99 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89b0d345081909a1d4475fa3876f5 completed March 29, 2026, 3:22 a.m.
NEDg Description generation batch_69c89d77b7cc81908120da0121c94537 completed March 29, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69c89ddd81a88190924d41529e94b06b completed March 29, 2026, 3:34 a.m.
Created at: March 27, 2026, 3:59 p.m.